A DNA barcode reference library for CITES listed Malagasy Dalbergia species

Abstract On Madagascar, the illegal and unsustainable exploitation and illegal international trade of Dalbergia (rosewood) precious woods remain a serious conservation problem. Members of this genus are at high risk of extinction as a consequence of logging, mining, and slash and burn agriculture. Morphological identification of these Malagasy species is difficult in the absence of flowers and fruits, especially in the case of cut trees, sawn wood, and finished product. In this study, we use molecular barcoding to identify the Dalbergia species with the intent to contribute to the control of their illegal trade. Thirty‐six Dalbergia samples representing 12 Malagasy species of which 11 have high commercial value, were collected to test the efficacy of a region of the plastid genome (rbcL) and a nuclear‐transcribed ITS for barcoding. These widely used markers, as well as DNA barcoding gaps, “best match” and “best close match” approaches, and the neighbor‐joining method were employed. All samples were amplified and sequenced using the two markers. Using a single locus, the “best match” and “best close match” approaches revealed that ITS has high discriminatory power within the tested Malagasy species. The combination of rbcL + ITS revealed 100% species discrimination. This study confirms that ITS alone and in combination with chloroplast barcode rbcL allow non‐ambiguous identification for the 12 species studied. The results contribute to the development of DNA barcoding as a useful tool to identify Malagasy Dalbergia and suggest that the approach developed should be expanded to all 56 potentially exploited species in reference to international CITES requirements and the sustainable management of valuable resources.


| INTRODUC TI ON
The wood of genus Dalbergia (Fabaceae), commonly known as rosewood and palisander, is highly appreciated because of its physical (hardness) and chemical properties (non-rotting), which making it high of commercial value (Bhagwat et al., 2015). Wood from Malagasy Dalbergia is mostly used for furniture and wood timber (Andrianoelina et al., 2009). The genus on Madagascar comprises 83 species, 55 of which are published, and 56 of these 83 species are large enough trees to be potential sources of commercially valuable wood (Madagascar Catalogue, 2022a, 2022b.
The Dalbergia species are distributed across all bioclimatic regions of Madagascar, including dry deciduous forests, humid forests, subhumid forests, and succulent woodlands (Madagascar Catalogue, 2022aCatalogue, , 2022b. At a global scale, the rate of deforestation and illegal logging in major timber-producing regions is a critical threat to biodiversity and forest ecosystems (Jiao et al., 2018). Since 2009, the illegal exploitation of these precious woods has continued to increase (Waeber & Wilmé, 2013). They are at high risk of extinction because of significant levels of logging, mining, and other human activities such as swidden (slash and burn) agriculture and charcoal production (Barrett et al., 2010;Styger et al., 2007). In 2013, Malagasy members of the genus were included in the Convention on International Trade in Endangered Species (CITES) Appendix II, and in 2016 because of the significant number of illegal exports, international trade of these species was suspended. The Convention on International Trade in Endangered Species has recommended that Madagascar makes progress on both the scientific and governance aspects on Decision 18.96 (CITES, 2016). The adulteration of forest products increases illegal trafficking and creates a serious problem for species management and conservation (Wiedenhoeft et al., 2019). More specifically, confusion in the identification of traded Dalbergia wood as compared to similar non-threatened species occurs (Hartvig et al., 2015), a situation that is accentuated by the lack of identification tools and a comprehensive reference library.
The genus Dalbergia, belonging to the family Fabaceae, subfamily Papilionoideae, is a taxonomically complex genus because in the absence of flowers and fruits it is difficult to distinguish species from one other based on morphological characteristics (Hassold et al., 2016), especially in the case of cut trees, sawn wood, and finished products. To obtain reliable identification, we have explored the use of molecular techniques. A global barcoding initiative to standardize molecular identifications using DNA protocols and regions has been agreed upon at the international level: The Consortium for the DNA Barcode of Life (CBOL) (CBOL Plant Working Group et al., 2009;Hebert et al., 2003). DNA barcoding has already been tested on Malagasy Dalbergia and on species from other countries, and was shown to be effective for their discrimination and identification using ITS (Hartvig et al., 2015;Phong et al., 2014;Yu et al., 2016) and rbcL and matK (Bhagwat et al., 2015;Hassold et al., 2016) gene regions. According by Hassold et al. (2016), DNA barcoding is an effective method for discriminating Malagasy Dalbergia from members of the genus occurring in other countries.
This study aims to (i) develop and test DNA barcoding as a tool for identifying Malagasy Dalbergia species using the chloroplastic region rbcL and a nuclear region ITS; and (ii) establish a reference database for 12 Malagasy Dalbergia species using barcodes to provide a basis for reliable and accurate identification in order to control their illegal exploitation and trade.

| Plant material
Since 2019, an EU-funded project has enabled the collection of material of Dalbergia throughout Madagascar; more than 2000 samples have been collected from all over the island (Figure 1). From these samples, 12 species (Figure 2)  following the manufacturer's protocol. The quality and concentration of DNA were evaluated using a nanodrop spectrophotometer (Thermo Fischer Scientific).
Gel images were obtained using an imaging system (Cleaver Scientific). Amplified PCR products were enzymatically purified using ExoSAP-IT™ (NEB). Fragments were prepared for sequencing using the BrilliantDye™ Terminator Cycle Sequencing Kit V3.1 (Nijmegen, Netherlands). The labeled products were purified with the ZR-96 DNA Sequencing Clean-up Kit (Zymo Research). The purified products were injected into the Applied Biosystems ABI 3500XL Genetic Analyzer (Thermo Fischer Scientific) with a 50 cm array, using POP7™ Polymer (Thermo Fischer Scientific). Samples were sequenced with the forward primer only. Wet lab experiments were performed at Inqaba Biotechnical Industries (Pty.) Ltd.
Sequence chromatogram viewing/analysis was performed using FinchTV analysis software.

| Data analysis
The DNA sequences for the ITS and rbcL regions of all samples were edited individually and manually using BioEdit software (Hall, 1999). After editing, the FASTA sequences were aligned using the Clustal-W algorithm with default parameters in Molecular Evolutionary Genetics Analysis-X (MEGA-X) (Kumar et al., 2018).
The alignments were manually adjusted as needed with BioEdit Software (Hall, 1999).
Intraspecific and interspecific distances were calculated using the MEGA-X software for the two individual gene regions and their combination. The sequence barcoding approach is very useful for discriminating sister species, where the amount of variation must be sufficient and not affecting their correct assignation based on intraspecific variation (Laiou et al., 2013). The barcoding gap is F I G U R E 1 Dalbergia tricolor photographed by Richard RANDR IAN AIV O calculated by the difference between the minimum interspecific distance and the maximum intraspecific distance, the former value must be higher than the latter (Zhang et al., 2015). If barcoding gap is detected, the species can be regarded as well differentiated (Meier et al., 2008). To evaluate species discrimination success, two methods were used, Best Match and Best Close Match in TaxonDNA software (Meier et al., 2006) and a neighbor-joining (NJ) tree-based approach (Saitou & Nei, 1987) in MEGA software; these were applied to the two single barcodes (rbcL and ITS) as well as the combination (ITS + rbcL) under the P-distance model.
For the tree-based method, unrooted NJ trees were constructed in MEGA-X with pairwise deletion and the Kimura 2-parameter model according to published sources on species discrimination (Hartvig et al., 2015;He et al., 2019;Kumar et al., 2018;Yu et al., 2017) and nodal support was determined through bootstrap analysis with 1000 replicates (Saitou & Nei, 1987). For the 36 specimens used, if all the conspecific individuals clustered in a single clade, this was considered a correct species discrimination.
TaxonDNA/SpeciesIdentifer 1.8 (Meier et al., 2006) was used for DNA barcoding analysis. This software calculates intraspecific and interspecific genetic distances, matching sequences, and clustering sequences based on pairwise distances. For analyzing identification rates of DNA barcodes, the criteria "best match", "best close match", and "all species barcodes" were employed (Meier et al., 2006). For the TaxonDNA analysis, we used the "best match" and the "best close match" functions in the software to test the species-level discrimination rates under the Kimura 2-parameter corrected distance  White et al. (1990) model for each barcode singly and all possible combinations of barcodes. The "best close match" method required a threshold value, which was calculated for each barcode from the pairwise summary.
All the results above the threshold were treated as "no match".

| Variation of barcoding markers
Genomic DNA extraction was successful for all 36 Dalbergia samples. PCR amplification was performed on the chloroplastic marker rbcL and one nuclear marker ITS. All PCR products were sequenced in a forward direction for ITS and rbcL. A total of 72 sequences were obtained from the 12 Dalbergia species. After trimming and alignment, the sequence lengths observed in all the analyzed samples included 428 bp for rbcL and 334 bp for ITS (

| Genetic distance and barcoding gap
Intraspecific and interspecific distances were calculated by the MEGA X software for two regions. The range of maximum intraspecific distance is 0.0044580-0.0187593 and the minimum interspecific distance is 0-0.218746 for each locus and combined (Table 4). average interspecific divergence was significantly higher than the corresponding intraspecific divergence for each of the loci, which was confirmed by the TaxonDNA analysis (Table 3).

| Application for species discrimination
TaxonDNA and NJ trees were used to discriminate between the 12 Dalbergia species studied. Considering the "best match" and "best close match" analysis with the TaxonDNA software, the highest discriminatory power between the species using the two markers is ITS (100%), whereas that for rbcL is lower (38.88%; Table 3). The combination of ITS + rbcL revealed 100% species discrimination (Table 3).
This study showed that among the candidate loci, ITS and the combination ITS + rbcL provided the best discriminating power between the tested Malagasy Dalbergia species.
On the basis of the methods used herein, the molecular grouping of individuals identified as the same species based on herbarium specimens and as belonging to the same clade, which indicates a correspondence between morphological and molecular identification.
On the basis of the NJ trees, the tested Dalbergia species are divided into two groups; one compromising members supergroup 1, as de-  Dalbergia species using ITS from several areas (Hartvig et al., 2015;He et al., 2019;Phong et al., 2014;Yu et al., 2016). In the subtribe Cassiinae (Fabaceae), ITS was suggested as the first option for DNA barcoding (Mishra et al., 2016). In the current study, the Best Match and Best Close Match analysis with the TaxonDNA software revealed that the discriminatory power of the two markers at the species level for 12 different Dalbergia taxa is 100% for ITS and 38.88% for rbcL. The rbcL region has been proposed as a barcode to discriminate among species because of its wide use, ease of amplification and alignment, and the existence of considerable online sequence data of numerous taxa (Hollingsworth et al., 2011;Newmaster et al., 2006). Our results are similar to those reported in work done on tropical tree species in India, where rbcL was found to have a high PCR and sequencing success rate, but a low species discrimination power of 43.6% (Tripathi et al., 2013).

| DISCUSS ION
For studies on other species of Dalbergia, the low discrimination power of rbcL has been observed by other researchers (Hassold et al., 2016;Liu et al., 2017). with ITS alone. For other genera of plants, ITS also has a high discriminatory power of 86.7% (Yang et al., 2012).
The current study also showed that, the combination of ITS + rbcL sequence data likewise provided 100% species identification. Similar results were found in other Dalbergia species using a combination of chloroplast and nuclear markers, ITS + matK+rbcL (Hartvig et al., 2015) and ITS + trnV + trnM1 + trnH-psbA and ITS2 + trnL (Yu et al., 2017). Previous research has indicated that using a single locus, ITS allows the highest discrimination of Dalbergia species although ITS in combination with rbcL and matK provides the best discrimination (Hartvig et al., 2015). The higher discriminatory power of the nuclear DNA region ITS over plastid barcodes has also been observed in Pterocarpus, with 85.1% correct species determination (Jiao et al., 2018).
Based on rbcL data from the 12 Malagasy Dalbergia species examined herein, the range of intraspecific distance was from 0 to 0.018759 and that of interspecific distance from 0 to 0.12937691 (Table 4). We did not identify a barcoding gap for rbcL ( Figure 3).
However, the mean interspecific divergence was significantly higher than the corresponding mean intraspecific divergence for each of the loci, which was confirmed by the TaxonDNA analysis (Table 3). Phylogenetic analysis can reveal whether species are monophyletic species, as well as providing important insights into species discriminations (Nithaniyal et al., 2014). Our phylogenetic trees can also be used for differentiating species with ITS and in combination with rbcL. Our analyses confirm that the species of Malagasy Dalbergia are divided into two distinct groups (Crameri, 2020;Hassold et al., 2016;Vatanparast et al., 2013). The recent studies performed on Malagasy members of this genus concur with our phylogenetic analyses in that supergroup 1 includes D. tricolor, D. chapelieri, D. pervillei, D. maritima, and D. normandii and supergroup 2 comprises D. monticola, D. peltieri, D. trichocarpa, D. bemarivensis, D. chlorocarpa, D. lemurica, and D. baronii (Crameri, 2020). Our results are consistent with and complementary to previous studies by Crameri (2020)  Referring to the results of the NJ phylogenetic trees with respect to the identification of Dalbergia from other parts of the world, the use of a single ITS locus showed a high identification rate (75%) and was even better when combined with other markers (100%) (He et al., 2019), which is similar to our findings. Taking into account the node support values, ITS alone and in combination with rbcL shows the same results for the discrimination of supergroup 1 species.
On the other hand, for supergroup 2, ITS alone gives better results with high node-support values in discriminating the closely related species of D. maritima and D. normandii. Elsewhere in the world, ITS failed to discriminate between Asian species D. tonkinensis and D.
odorifera (Yu et al., 2016). One of the important roles of a sequence database is to help determine the identity of unidentified material (Meier et al., 2006). To test the performance of molecular identification, it is necessary to perform a blind test in which an unknown sample is analyzed and sequenced and then compared with the available sequences of previously identified samples.
Madagascar is still facing a difficult task to control exportation of its own precious hardwoods and to control illegal exploitation

ACK N OWLED G M ENTS
The research was financially supported by the European Union pro- We are grateful to botanists and guides for collecting samples in the field and for general assistance. We also thank Nicholas Wilding, Simon Crameri, Nivo Rakotonirina, and Sylvie Andriambololonera for their help in morphological species identifications. We thank Inqaba Biotechnical Industries, specifically Oliver Preisig, Christiaan Labuschagne, Simon Lashmar, and Acclaim Moila for laboratory assistance in South Africa. The authors are grateful to Steve Goodman for revising the English and improving this manuscript. Finally, we thank the two anonymous reviewers provided useful comments on earlier versions of the manuscript.

CO N FLI C T O F I NTER E S T S TATEM ENT
The authors declare no conflicts of interest.